Ovarian Hormones and Addictive Behaviour Vulnerability: Insights From Preclinical Studies

Abstract

Substance use disorder constitutes a global health challenge. Preclinical investigations into addiction heavily rely on animal models to explore the underlying biological mechanisms of addictive disorders, with a particular emphasis on understanding the etiological factors influencing drug intake. Exploring sex differences across various phases of addiction has revealed a heightened vulnerability in females. This study systematically reviews the impact of ovarian hormones on the consumption of psychoactive substances in rodents, adhering to the PRISMA 2009 protocol. Our findings underscore the significant role of ovarian hormones, particularly oestrogen, in augmenting drug consumption among female rodents. Notably, with heroin, it was observed that progesterone, rather than oestrogen, facilitated increased consumption in female rodents. The susceptibility to addiction influenced by oestrogen is accentuated across distinct phases, and the molecular mechanisms form a complex interplay that significantly influences addictive behaviours. By bringing together these findings, we aim to establish a strong foundation for future studies. This work may guide clinical investigations in developing more effective prevention or treatment strategies that address the unique vulnerabilities of females to substance use disorders.

Keywords: addiction; drug consumption; oestrogen; preclinical studies; progesterone; psychoactive substances; substance use disorder; systematic review.

FIGURE 1

PRISMA flow diagram. Flowchart of the studies included after passing the screening and selection process.

FIGURE 2

Graphical description of quantitative aspects of the reviewed literature. The studies were classified according to the following characteristics: (A) model of drug administration: forced administration (FA), self‐administration (SA), conditioned place preference (CPP) or use of more than one model; (B) strain and type of rodent used for the studies; (C) life stage of the animals considered for the studies; and (D) type of main comparison of the studies: sex differences, sex and hormonal differences, sex and other types of comparison and hormonal differences. Abbreviations: 4‐MMC: 4‐methylephedrone, COC: cocaine, EtOH: ethanol, FEN: fentanyl, HER: heroin, MA: methamphetamine, MDMA: 4‐methylenedioxymethamphetamine, NIC: nicotine, MORPH: morphine, THC: tetrahydrocannabinol, OXY: oxycodone.

FIGURE 3

Schematic representation of the dopaminergic reward signalling pathways and their interaction with oestrogen signalling. PAS compounds (COC, MA and NIC) competitively inhibit DAT upon reaching the brain, thereby preventing neuronal reuptake of DA and promoting its synaptic accumulation. D1 and D2 receptors are associated with G proteins; D1‐associated subunits promote signal exchange with other pathways such as MAPK‐MEPK‐ERK and CREB, a gene regulator potentially involved in the synaptic remodelling of receptor desensitization and enhancing the memory effects of E2 in response to membrane‐initiated signalling events. Furthermore, PAS (Ket, EtOH, Her, Remifen, THC, Win and CP5594) can modulate glutamate release, directly or indirectly, through D1‐R activation, leading to an increase in AMPAR and NMDA receptor trafficking. Alongside, the neurosteroid E2 binds to its receptor and other transmembrane receptors (such as metabotropic glutamatergic receptor ‘mGLUR5’) and initiates kinase signalling cascades that lead to additional upregulatory processes, such as protein synthesis and NMDA channel phosphorylation; all of which contribute to modulations in synaptic function, neuronal plasticity and glutamatergic transmission. Elevated ACTH and corticosterone during proestrus (high‐oestrogen phase) further interact with DA pathways, amplifying synaptic modulation. Abbreviations: ACTH: adrenocorticotropic hormone, AMPAR: α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor, COC: cocaine, CP55940: cannabinoid 1 agonist, CREB: cAMP response element‐binding, D1R: dopamine receptor, DA: dopamine, DAT: dopamine transporters, E2: estrone, ERK: extracellular‐signal‐regulated kinase, EtOH: ethanol, HER: heroin, Ket: ketamine, MA: methamphetamine, MAPK: mitogen‐activated protein kinases, NMDA: N‐methyl‐D‐aspartate, NIC: nicotine, FA: forced administration, PASs: psychoactive substances, SA: self‐administration, THC: tetrahydrocannabinol, WIN: CB1 receptor agonist WIN55,212‐2. Figure modelled after [70, 71]. Created with BioRender.com.

FIGURE 4

Mechanisms of methamphetamine and cocaine on dopamine transport and neuronal excitability. MA is the substrate for DAT, which competes with DA and causes increased DA extracellular, while it alters neuronal excitability by reducing the amplitude of calcium‐activated potassium currents (BK channels). In addition, MA modulates DA release through activation of σ1R receptors in the endoplasmic reticulum of cells of the NAc, impairing the function of the VMAT2 via oxidation of a cysteine residue. On the other hand, COC inhibits DA reuptake by blocking DAT in its outward‐facing conformation and inducing its intracellular translocation, mediated by SYNJ1. Abbreviations: ACTH: adrenocorticotropic hormone, AMPAR: α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor, COC: cocaine, CP55940: cannabinoid 1 agonist, CREB: cAMP response element‐binding, CRH: corticotropin‐releasing hormone, CRHR: corticotropin‐releasing hormone receptor, D1R: dopamine receptor, DA: dopamine, DAG: diacylglycerol, DAT: dopamine transporters, E2: estrone, ER: oestrogen receptor, ERK: extracellular‐signal‐regulated kinase, EtOH: ethanol, FA: forced administration, GLU: glutamate, HER: heroin, IP3: 1,4,5‐trisphosphate, Ket: ketamine, m‐GluR5: metabotropic glutamate receptor 5, MA: methamphetamine, MAPK: mitogen‐activated protein kinases, NMDA: N‐methyl‐D‐aspartate, NIC: nicotine, PASs: psychoactive substances, PCL: phospholipase C, SA: self‐administration, SYNJ1: synaptojanin‐1, THC: tetrahydrocannabinol, VMAT2: vesicular monoamine transporter 2, WIN: CB1 receptor agonist WIN55,212‐2. Figure modelled after [72, 73, 74]. Created with BioRender.com.

FIGURE 5

Postulated interaction among oestrogen, progesterone and opioid receptors. Estradiol (ES), when binding to its mER, can modify ionotropic conductance by promoting the phosphorylation of ionotropic receptors and the decoupling of OR from their ion channels. It also triggers intracellular signalling interactions via the G protein subunits (α, β and γ) to which it is coupled. The activation of PLC catalyses the conversion of membrane‐bound PIP2 into IP3 and DAG. Subsequently, IP3 promotes the release of Ca+, starting calcium‐dependent signalling. DAG activates PKC, which in turn activates AC, increases cAMP and can phosphorylate ion channels and cAMP response CREB. ES can also bind to nuclear RE dimers, such as the ERE in DNA, promoting the transcription of specific genes, including the upregulation of μ‐opioid receptors (MOR) and leading to reduced opioid intake. PRO binds to its mPRO and can alter gene transcription regulated by second messengers (cAMP/PKA and Ca+/PKC) and signal transduction pathways MAPK, resulting in the phosphorylation of nuclear transcription factors. PRO can also bind to its nuclear receptor, contributing to changes in gene transcription, such as the downregulation of ORs. Additionally, ALLO modulates the activity of synaptic GABA_A receptors, facilitating chloride ion (Cl⁻) entry and regulating neuronal excitability. Abbreviations: ALLO: allopregnanolone, AC: adenylate cyclase, CREB: element‐binding proteins, ERE: oestrogen response element, ES: oestrogen, GABA: gamma‐aminobutyric acid, GABA_AR: GABA_A receptor, IP3: inositol 1,4,5‐trisphosphate, mER: membrane oestrogen receptor, MAPK: mitogen‐activated protein kinases, mPRO: progesterone membrane receptor, ORs: opioid receptors, PCL: phospholipase C, PKC: protein kinase C, PIP2: phosphatidylinositol 4,5‐bisphosphate, PRO: progesterone. Figure modelled after [75, 76]. Created with BioRender.com.

FIGURE 6

Evaluation of the methodological quality and assessment of the risk of bias. The bars represent the percentage of the articles found in each category.